Fetching the paper…
Reading the bibliography…
Developing a dialogue agent that is capable of making autonomous decisions and communicating by natural language is one of the long-term goals of machine learning research.
An iterative design methodology for user-friendly natural language office information applications
Kelley, John F · 1984
Earlier work this paper cites.
Simple statistical gradient-following algorithms for connectionist reinforcement learning
Williams, Ronald J · 1992
Earlier work this paper cites.
Long short-term memory
Hochreiter, Sepp and Schmidhuber, Jürgen · 1997
Earlier work this paper cites.
Foundations of Rational Agency , chapter Speech Acts for Dialogue Agents
Traum, David R · 1999
Earlier work this paper cites.
Bleu: a method for automatic evaluation of machine translation
Papineni, Kishore, Roukos, Salim, Ward, Todd, and Zhu, Wei-Jing · 2002
Earlier work this paper cites.
On actor-critic algorithms
Konda, Vijay R. and Tsitsiklis, John N · 2003
Earlier work this paper cites.
Learning syntactic patterns for automatic hypernym discovery
Snow, Rion, Jurafsky, Daniel, and Ng, Andrew Y · 2004
Earlier work this paper cites.
On-line policy optimisation of bayesian spoken dialogue systems via human interaction
Gašić, Milica, Breslin, Catherine, Henderson, Matthew, Kim, Dongho, Szummer, Martin, Thomson, Blaise, Tsiakoulis, Pirros, and Young, Steve · 2013
Earlier work this paper cites.
Pomdp-based statistical spoken dialog systems: A review
Young, Steve, Gašić, Milica, Thomson, Blaise, and Williams, Jason D · 2013
Earlier work this paper cites.
Decoder integration and expected bleu training for recurrent neural network language models
Auli, Michael and Gao, Jianfeng · 2014
Earlier work this paper cites.
Word-based dialog state tracking with recurrent neural networks
Henderson, Matthew, Thomson, Blaise, and Young, Steve · 2014
Earlier work this paper cites.
Adam: A method for stochastic optimization
Kingma, Diederik P. and Ba, Jimmy · 2014
Earlier work this paper cites.
Stochastic backpropagation and approximate inference in deep generative models
Kingma, Diederik P. and Welling, Max · 2014
Earlier work this paper cites.
Semi-supervised learning with deep generative models
Kingma, Diederik P., Mohamed, Shakir, Rezende, Danilo J., and Welling, Max · 2014
Earlier work this paper cites.
Neural variational inference and learning in belief networks
Mnih, Andriy and Gregor, Karol · 2014
Earlier work this paper cites.
Recurrent models of visual attention
Mnih, Volodymyr, Heess, Nicolas, Graves, Alex, and kavukcuoglu, koray · 2014
Cited alongside, same era.
Sequence to sequence learning with neural networks
Sutskever, Ilya, Vinyals, Oriol, and Le, Quoc V · 2014
Cited alongside, same era.
Neural machine translation by jointly learning to align and translate
Bahdanau, Dzmitry, Cho, Kyunghyun, and Bengio, Yoshua · 2015
Cited alongside, same era.
Generating sentences from a continuous space
Bowman, Samuel R., Vilnis, Luke, Vinyals, Oriol, Dai, Andrew M., Józefowicz, Rafal, and Bengio, Samy · 2015
Cited alongside, same era.
Retrofitting word vectors to semantic lexicons
Faruqui, Manaal, Dodge, Jesse, Jauhar, Sujay Kumar, Dyer, Chris, Hovy, Eduard, and Smith, Noah A · 2015
Cited alongside, same era.
Machine learning for dialog state tracking: A review
Henderson, Matthew · 2015
Cited alongside, same era.
Semantic parsing with semi-supervised sequential autoencoders
Kočiský, Tomáš, Melis, Gábor, Grefenstette, Edward, Dyer, Chris, Ling, Wang, Blunsom, Phil, and Hermann, Karl Moritz · 2016
Later among the works it cites.
Language as a latent variable: Discrete generative models for sentence compression
Miao, Yishu and Blunsom, Phil · 2016
Later among the works it cites.
Neural variational inference for text processing
Miao, Yishu, Yu, Lei, and Blunsom, Phil · 2016
Later among the works it cites.
A hierarchical latent variable encoder-decoder model for generating dialogues
Serban, Iulian V., Sordoni, Alessandro, Lowe, Ryan, Charlin, Laurent, Pineau, Joelle, Courville, Aaron, and Bengio, Yoshua · 2016
Later among the works it cites.
Mastering the game of go with deep neural networks and tree search
Silver, David, Huang, Aja, Maddison, Chris J, Guez, Arthur, Sifre, Laurent, Van Den Driessche, George, Schrittwieser, Julian, Antonoglou, Ioannis, Panneershelvam, Veda, Lanctot, Marc, et al · 2016
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Deep visual-semantic alignments for generating image descriptions
Karpathy, Andrej and Fei-Fei, Li · 2015
Cited alongside, same era.
Hierarchical neural network generative models for movie dialogues
Serban, Iulian Vlad, Sordoni, Alessandro, Bengio, Yoshua, Courville, Aaron C., and Pineau, Joelle · 2015
Cited alongside, same era.
Neural responding machine for short-text conversation
Shang, Lifeng, Lu, Zhengdong, and Li, Hang · 2015
Cited alongside, same era.
Learning from real users: Rating dialogue success with neural networks for reinforcement learning in spoken dialogue systems
Su, Pei-Hao, Vandyke, David, Gasic, Milica, Kim, Dongho, Mrksic, Nikola, Wen, Tsung-Hsien, and Young, Steve · 2015
Cited alongside, same era.
A neural conversational model
Vinyals, Oriol and Le, Quoc V · 2015
Cited alongside, same era.
Semantically conditioned lstm-based natural language generation for spoken dialogue systems
Wen, Tsung-Hsien, Gasic, Milica, Mrkšić, Nikola, Su, Pei-Hao, Vandyke, David, and Young, Steve · 2015
Cited alongside, same era.
On-line active reward learning for policy optimisation in spoken dialogue systems
Su, Pei-Hao, Gasic, Milica, Mrkšić, Nikola, Rojas Barahona, Lina M., Ultes, Stefan, Vandyke, David, Wen, Tsung-Hsien, and Young, Steve · 2016
Later among the works it cites.
Conditional generation and snapshot learning in neural dialogue systems
Wen, Tsung-Hsien, Gasic, Milica, Mrkšić, Nikola, Rojas Barahona, Lina M., Su, Pei-Hao, Ultes, Stefan, Vandyke, David, and Young, Steve · 2016
Later among the works it cites.
Dialog-based language learning
Weston, Jason E · 2016
Later among the works it cites.
Learning end-to-end goal-oriented dialog
Bordes, Antoine and Weston, Jason · 2017
Closest in time.
Latent variable dialogue models and their diversity
Cao, Kris and Clark, Stephen · 2017
Closest in time.
beta-vae: Learning basic visual concepts with a constrained variational framework
Higgins, Irina, Matthey, Loic, Pal, Arka, Burgess, Christopher, Glorot, Xavier, Botvinick, Matthew, Mohamed, Shakir, and Lerchner, Alexander · 2017
Closest in time.
Dialogue learning with human-in-the-loop
Li, Jiwei, Miller, Alexander H., Chopra, Sumit, Ranzato, Marc’Aurelio, and Weston, Jason · 2017
Closest in time.
Neural belief tracker: Data-driven dialogue state tracking
Mrkšić, Nikola, Ó Séaghdha, Diarmuid, Wen, Tsung-Hsien, Thomson, Blaise, and Young, Steve · 2017
Closest in time.
A network-based end-to-end trainable task-oriented dialogue system
Wen, Tsung-Hsien, Vandyke, David, Mrkšić, Nikola, Gašić, Milica, M. Rojas-Barahona, Lina, Su, Pei-Hao, Ultes, Stefan, and Young, Steve · 2017
Closest in time.